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listDatasets

Retrieve all available datasets from Axiom to view and manage your data sources.

Instructions

List all available Axiom datasets

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler function for the 'listDatasets' tool. It checks rate limiting, lists all Axiom datasets using client.datasets.list(), and returns them as a JSON string in the MCP response format.
    async () => {
      const remainingTokens = datasetsLimiter.tryRemoveTokens(1);
      if (!remainingTokens) {
        throw new Error("Rate limit exceeded for dataset operations");
      }
    
      try {
        const datasets = await client.datasets.list();
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify(datasets),
            },
          ],
        };
      } catch (error) {
        throw new Error(`Failed to list datasets: ${error.message}`);
      }
    }
  • index.js:149-173 (registration)
    The registration of the 'listDatasets' tool using server.tool(), including name, description, empty input schema, and inline handler function.
    server.tool(
      "listDatasets",
      "List all available Axiom datasets",
      {},
      async () => {
        const remainingTokens = datasetsLimiter.tryRemoveTokens(1);
        if (!remainingTokens) {
          throw new Error("Rate limit exceeded for dataset operations");
        }
    
        try {
          const datasets = await client.datasets.list();
          return {
            content: [
              {
                type: "text",
                text: JSON.stringify(datasets),
              },
            ],
          };
        } catch (error) {
          throw new Error(`Failed to list datasets: ${error.message}`);
        }
      }
    );
  • The input schema for the 'listDatasets' tool, which is empty as it takes no parameters.
    {},
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It states the action ('List all available') but doesn't cover critical traits like pagination, rate limits, authentication needs, or what 'available' means (e.g., permissions, status). This leaves significant gaps for a tool that likely interacts with datasets.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with zero waste—'List all available Axiom datasets' directly conveys the core purpose without extraneous details. Every word earns its place, making it highly efficient and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (0 parameters, no output schema), the description is minimally adequate but lacks depth. Without annotations or output schema, it should ideally mention return format (e.g., list of dataset names/IDs) or behavioral constraints. It's complete enough for basic understanding but misses contextual nuances.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, earning a baseline high score. It could be a 5 if it explicitly noted the lack of parameters, but the current brevity is sufficient.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('List') and resource ('available Axiom datasets'), making the purpose immediately understandable. It doesn't distinguish from sibling tools like getDatasetInfoAndSchema or queryApl, which prevents a perfect score, but the core functionality is well-defined.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like getDatasetInfoAndSchema (for detailed info) or queryApl (for querying data). It lacks explicit context, prerequisites, or exclusions, leaving the agent to infer usage from tool names alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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